Peer Review #1 of "The effects of the gender-culture interaction on self-reports of depressive symptoms: cross-cultural study among Egyptians and Canadians (v0.1)"
Bibliographic record
Abstract
Purpose: Research in depression has revealed differences in the way depressed individuals across cultures report their symptoms.This literature also points to possible differences in symptom reporting patterns between men and women.Using data from a larger dataset (Beshai et al., 2016), the current study examined whether non-depressed and depressed Egyptian and Canadian men and women differed in their self-report of the various domains of the Beck Depression Inventory -II (BDI-II).Method: We recruited a total of 131 depressed and non-depressed participants from both Egypt (n = 29 depressed; n = 29 non-depressed) and Canada (n = 35 depressed; n = 38 non-depressed).Depression status was ascertained using a structured interview.All participants were asked to complete the BDI-II along with other self-report measures of depression.BDI-II items were divided into two subscales in accordance with Dozois and Dobson's (1998) factor analysis: cognitive-affective and somatic-vegetative subscales.Results: We found a significant three-way interaction effect on the cognitive-affective (F(1,121) = 9.51, p = .003)and main effect of depression status on somatic-vegetative subscales (F(1,121) = 42.80,p < .001).Post hoc analyses revealed that depressed Egyptian men reported lower scores on the cognitive-affective subscale of the BDI-II compared to their depressed Canadian male counterparts.Conclusions: These results suggest that males across cultures may differentially report cognitive symptoms of depression.These results also suggest that clinicians and clinical scientists need to further examine the interaction effect of culture and gender when investigating self-reported symptoms of depression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.174 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.257 | 0.104 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".